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A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development

Source: Bulletin of the American Meteorological Society:;2019:;volume 100:;issue 006:;page 1091

Author(s): Subramanian, Aneesh; Juricke, Stephan; Dueben, Peter; Palmer, Tim

Publisher: American Meteorological Society

Abstract: AbstractNumerical weather prediction and climate models comprise a) a dynamical core describing resolved parts of the climate system and b) parameterizations describing unresolved components. Development of new subgrid-scale ...

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Improving Medium-Range Ensemble Weather Forecasts with Hierarchical Ensemble Transformers

Source: Artificial Intelligence for the Earth Systems:;2024:;volume( 003 ):;issue: 001

Author(s): Bouallègue, Zied Ben; Weyn, Jonathan A.; Clare, Mariana C. A.; Dramsch, Jesper; Dueben, Peter; Chantry, Matthew

Publisher: American Meteorological Society

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Machine Learning for Earth System Observation and Prediction

Source: Bulletin of the American Meteorological Society:;2021:;volume( 102 ):;issue: 004

Author(s): Bonavita, Massimo;Arcucci, Rossella;Carrassi, Alberto;Dueben, Peter;Geer, Alan J.;Le Saux, Bertrand;Longépé, Nicolas;Mathieu, Pierre-Philippe;Raynaud, Laure

Publisher: American Meteorological Society

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A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development

Improving Medium-Range Ensemble Weather Forecasts with Hierarchical Ensemble Transformers

Machine Learning for Earth System Observation and Prediction

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A Stochastic Representation of Subgrid Uncertainty for Dynamical Core Development

Improving Medium-Range Ensemble Weather Forecasts with Hierarchical Ensemble Transformers

Machine Learning for Earth System Observation and Prediction